A Model Context Protocol (MCP) server that connects AI assistants to the Spotify Web API. Enables natural language access to Spotify playback
Connect Kotlin For Spotify to Claude, Cursor or any other MCP client and it stops being a tab you switch to. A Model Context Protocol (MCP) server that connects AI assistants to the Spotify Web API. Enables natural language access to Spotify playback, search, playlists, and user profile data — ideal for building LLM-integrated music assistants. The kotlin for spotify mcp server is what makes that connection.
A Kotlin implementation of a Model Context Protocol (MCP) server that integrates with the Spotify Web API. This server provides tools for controlling Spotify playback, managing playlists, and retrieving user information through a standardized interface.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.
Configuration is passed through the environment: SPOTIFY_CLIENT_ID, SPOTIFY_CLIENT_SECRET. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. It is maintained by Carrieukie; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Variable | Description | Required |
|---|---|---|
| SPOTIFY_CLIENT_ID | Configuration value read at startup. | Optional |
| SPOTIFY_CLIENT_SECRET | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
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Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
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The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.